Performance evaluation of social network anomaly detection using a moving window–based scan method

[1]  George C. Runger,et al.  Monitoring Temporal Homogeneity in Attributed Network Streams , 2016 .

[2]  William H. Woodall,et al.  Modeling and Detecting Change in Temporal Networks via a Dynamic Degree Corrected Stochastic Block Model , 2016 .

[3]  Kathleen M. Carley,et al.  Measuring Temporal Patterns in Dynamic Social Networks , 2015, ACM Trans. Knowl. Discov. Data.

[4]  Rassoul Noorossana,et al.  An overview of dynamic anomaly detection in social networks via control charts , 2018, Qual. Reliab. Eng. Int..

[5]  Kwok-Leung Tsui,et al.  Detecting node propensity changes in the dynamic degree corrected stochastic block model , 2018, Soc. Networks.

[6]  M. R. Reynolds,et al.  A CUSUM Chart for Monitoring a Proportion with Autocorrelated Binary Observations , 2009 .

[7]  David J. Marchette,et al.  Scan Statistics on Enron Graphs , 2005, Comput. Math. Organ. Theory.

[8]  Ronald D Fricker,et al.  Comparing syndromic surveillance detection methods: EARS' versus a CUSUM‐based methodology , 2008, Statistics in medicine.

[9]  Andrea Montanari,et al.  Finding One Community in a Sparse Graph , 2015, Journal of Statistical Physics.

[10]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Danai Koutra,et al.  Graph based anomaly detection and description: a survey , 2014, Data Mining and Knowledge Discovery.

[12]  L. R. Dice.  Measures of the Amount of Ecologic Association Between Species , 1945 .

[13]  Jaime A. Camelio,et al.  A Spatiotemporal Method for the Monitoring of Image Data , 2012, Qual. Reliab. Eng. Int..

[14]  P. Santhi Thilagam,et al.  Mining social networks for anomalies: Methods and challenges , 2016, J. Netw. Comput. Appl..

[15]  Xiuzhen Zhang,et al.  Anomaly detection in online social networks , 2014, Soc. Networks.

[16]  Mark E. J. Newman,et al.  Stochastic blockmodels and community structure in networks , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[17]  R. Fricker.  Some methodological issues in biosurveillance , 2011, Statistics in medicine.

[18]  Kathleen M. Carley.  Dynamic Network Analysis , 2003 .

[19]  William H. Woodall,et al.  An overview and perspective on social network monitoring , 2016, ArXiv.

[20]  Ronald D. Fricker,et al.  Comparing Directionally Sensitive MCUSUM and MEWMA Procedures with Application to Biosurveillance , 2008 .

[21]  Steve Harenberg,et al.  Anomaly detection in dynamic networks: a survey , 2015 .